AI Biodiversity Monitoring Developer

About the role

Responsibilities

• Improve classification accuracy on failure modes: low-light, occlusion, rare species
• Build active learning pipelines to efficiently prioritize ambiguous images for review
• Implement few-shot classification for rare species with limited training data
• Design out-of-distribution detection for novel species not in the training set
• Create evaluation frameworks using ecologist-validated ground truth
• Collaborate with field teams on data collection strategies for underrepresented species

Requirements

• 3+ years in computer vision engineering with classification or detection experience
• Experience with active learning, few-shot learning, or out-of-distribution detection
• Strong PyTorch skills and familiarity with fine-tuning pre-trained vision models
• Ability to work with small, imbalanced labeled datasets
• Genuine interest in conservation technology or environmental monitoring

Benefits

• Fully remote across EU time zones
• Mission-driven conservation work
• 30 days PTO
• Health insurance
• Annual field visit to one of our conservation project sites

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